Data Science - Top 10 Countdown of Certification & Training Programs (#7)

Colleagues, after building your data wrangling and Python skills, our #7 recommendations on our Top 10 Countdown is Data Science Fundamentals Part 2 - Machine Learning and Statistical Analysis. This intermediate-level program will equip you in how to get up and running with a Python data science environment, the basics of the data science process and what each step entails, how (and why) to perform exploratory data analysis in Python with the pandas library, the theory of statistical estimation to make inferences from your data and test hypotheses, the fundamentals of probability and how to use scipy to work with distributions in Python, how to build and evaluate machine learning models with scikit-learn, the basics of data visualization and how to communicate your results effectively and the importance of creating reproducible analyses and how to share them effectively. Training modules include: 1) Exploring Data–Analysis and Visualization, 2) Making Inferences–Statistical Estimation and Evaluation, 3) Statistical Modeling and Machine Learning. The program concludes by discussing the differences between and nuances of statistics, modeling, and machine learning. I provide an overview of the various types of models and algorithms used for machine learning and introduce how to leverage scikit-learn–a robust machine learning library in Python–to make predictions.

Enroll today (teams & execs welcome): https://tinyurl.com/2rhu873h 

Much career success, Lawrence E. Wilson - Artificial Intelligence Academy (share & subscribe) [ ] 

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